Cited by 68Intelligent Tutoring Systems and Adaptive LearningOnline Learning and AnalyticsEducational Technology and Assessment

A novel adaptive e-learning model based on Big Data by using competence-based knowledge and social learner activities

Birjali, Marouane, Beni-Hssane, Abderrahim, Erritali, Mohammed·2018·Applied Soft Computing

Integrity signals

Registry

Crossref · 10.1016/j.asoc.2018.04.030

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61 of 61 references verified0 citation errors · 0 not checkable

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  • In [32], evolutionary algorithm, ant colony optimization, and social network analysis were used to determine future educational objectives, generate adaptive learning paths, and assign learning rhythm.

    “Evolutionary algorithm used for determining relevant future educational objectives using an adequate learner e-assessment method.ACO is used for generating an adaptive learning path for each learner.SNA is used for determining the learner's motivation and social productivity to assign a specific learning rhythm to each learner.”

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Authors
Birjali, M., Beni-Hssane, A., & Erritali, M.
Affiliations
  • Chouaib Doukkali University (MA)
  • Université Sultan Moulay Slimane (MA)
Corresponding author
Birjali, Marouane
Venue
Applied Soft Computing
Publisher
Elsevier BV
Published
2018-08
Volume
69
Pages
14-32
ISSN
1568-4946 (ISSN-L)
OpenAlex
W2802820061
Cited by
68
References
61
Citations by year
2025: 3 · 2024: 8 · 2023: 12 · 2022: 13 · 2021: 10 · 2020: 11 · 2019: 9 · 2018: 2
FWCI
4.48
Type
journal article
Language
en
Open access
closed
Locations
Applied Soft Computing (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Physical Sciences › Computer Science › Information Systems › Educational Technology and Assessment
Keywords
adaptive e-learning, big data in education, personalized learning paths, student assessment, MapReduce, genetic algorithm, ant colony optimization, social network analysis, student motivation, learning rhythms

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